Posts tagged as: Features extraction

Robots working in industrial applications need visual feedback. This is used to navigate, identify parts, collaborate with humans and fuse visual information with other sensors to enhance their location information. This is the reason for the use of machine vision in industrial applications. Robo...

One ml of human blood contains roughly 5 million red blood cells. This huge quantity is only a fraction of what is found in one ml of blood, which contains roughly 60% fluid (plasma) and the remaining white cells, red blood cells and platelets. The composition of blood is examined routinely in ho...

Reconstruction of the three-dimensional surface of an object based on single view 2-D sequence of images is a highly challenging task. Challenges stem in part from the construction of a template representing the object, or more formally, incorporating knowledge to restrict the shape space. The po...

Retinopathy of prematurity (ROP) is a leading cause of blindness in infants. ROP (or Terry syndrome) is a disease of the eye affecting prematurely-born, low birthweight infants having received intensive neonatal care which includes oxygen therapy. Oxygen toxicity causes abnormal growth of retinal...

Digitalization of money transfer is a must in the current state of banking operations. Clients have various ways to perform transactions, such as credit, wiring money, and so forth. However, the banking systems and many businesses accepts checks as a formal means of money transfer. Checks still a...

The explosion of data collection techniques and resources is a known phenomenon of the current day and age. Human analysis of such large datasets is largely infeasible and the vast amount of information can only be dealt systematically and efficiently by algorithmic means. The so called ‘big data...

In search for a pattern in an image, a video or a signal, one has to consider several sources of bias, noise and uncertainties. Such uncertainties are the result of acquisition of natural signals such as outdoors images in non-sterile and poorly lit conditions, possibly containing smear, blurs, a...

Testing a set of images for similarity has long been a task of image processing computer vision and machine learning. The plethora of tools and techniques suggested to treat such task stems from the ever expanding definition of similarity. For some applications, similarity in color might suffice;...

Classification problems in image and signal analysis require, on the algorithmic side, to take into account complex information embedded in the data. Images might contain many thousands of pixel values in several color channels; their correlation and relationship characterizes the class and enabl...

Image and object recommender systems have been developed along with the Internet itself. The recommender systems are constructed to assist user’s navigation through the variety of content and products (videos, images or objects sold on a website) by correlating user preferences with the item’s ch...

Studying the behavior of cells in-vitro is one of the most fundamental research tools in biology. Studies conducted under the microscope improve our understanding of cell-cell interaction, motility, and reaction to different biochemical conditions. In addition, cell counting and sorting, which ar...

Quantitative Coronary Analysis Quantitative Coronary Analysis (QCA) refers to the set of methods used to measure the diameter of arteries. The set of tools and algorithms for QCA have been developed for the purpose of lesion and stenosis detection and analysis, and promote rational clinical decis...

What’s the Difference between Computer Vision, Image Processing and Machine Learning? Computer vision, image processing, signal processing, machine learning – you’ve heard the terms but what’s the difference between them? Each of these fields is based on the input o...